Proceedings of the IEEE 39th Annual Computers, Software and Applications Conference (COMPSAC '15),
Part I: The 2015 Stephen S. Yau Academic Symposium, IEEE Computer Society, pp. 11-16 (2015)

Slope-based Sequencing Yardstick for
Analyzing Unsatisfactory performance of multithreaded programs:
An SSYAU trend estimation approach to performance bug localization 1, 2

W.K. Chan 3 , T.H. Tse 4 Shangru Wu 3 , Y.T. Yu 5 , and Zhenyu Zhang 6

[paper from IEEE Xplore | paper from IEEE digital library | technical report TR-2015-06]

 ABSTRACT

As users are increasingly concerned about energy efficiency, they are also increasingly intolerant of performance anomalies of programs that may cause significant energy waste. Bug localization is a bottleneck in the development of multithreaded programs. Although both static and dynamic performance bug localization techniques have been proposed, they cannot handle performance anomalies with unforeseen patterns, and cannot work well if the concept of performance anomaly is fuzzy or evolves over time for the same program. We propose a novel model-based approach to performance bug localization. The approach is based on curve fitting and trend estimation over program executions with performance data. We describe our trend estimation model and illustrate it with the result of a case study on locating three real-world performance bugs in MySQL.

Keywords: performance bug, model-based approach, multithreaded program, bug localization

1. The acronym of our approach is "SSYAU" by design to celebrate Professor Stephen S. Yau's 80th birthday.
2. This research is supported in part by the General Research Fund of the Research Grants Council of Hong Kong (project nos. 11201114, 125113, 716612, and 717811) and the National Natural Science Foundation of China (project no. 61379045).
3. Department of Computer Science, City University of Hong Kong, Tat Chee Avenue, Hong Kong.
4. Department of Computer Science, The University of Hong Kong, Pokfulam, Hong Kong.
5. (Corresponding author.)
Department of Computer Science, City University of Hong Kong, Tat Chee Avenue, Hong Kong.
Email:
6. State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China.

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